Cyber-physical systems are becoming increasingly complex. In these advanced systems, the different engineering domains involved in the design process become more and more intertwined. In these situations, a traditional (sequential) design process becomes inefficient in finding good designs options. Instead, an integrated approach is needed where parameters in both the control and embedded domain can be chosen, evaluated and optimized to have a good solution in both domains. However, in such an approach, the combined design space becomes vast. As such, methods are needed to mitigate this problem. In this paper, we show how domain knowledge can be used to guide the design-space exploration process for an advanced control system and its deployment on embedded hardware. We use domain knowledge, captured in an ontology, to reason about the relationships between parameters in the different domains. This leads to a stepwise design space-exploration process where this domain knowledge is used to quickly reduce the design space to a subset of likely good candidates. In this process, we make use of cross-domain evaluation to find feasible design options with good system-level performance.
The loads to which a wind turbine gearbox is subjected during its lifetime can be a valuable source of information to decrease maintenance cost and downtime through enhanced monitoring, control and design. However, this load information is difficult to acquire since suitable direct load sensors are intrusive and expensive. Therefore, this paper focuses on indirect load measurement through a virtual sensing algorithm. The resulting virtual load sensor estimates the incoming load on the low speed planetary stage of the gearbox by combining strain measurements on the external surface of the ring gear with a physics-based model. The algorithm is deployed for real-time execution on low-cost embedded hardware to make a cost-effective load sensor. The effect of the configuration parameters of the virtual load sensor on the execution time and memory usage is examined in order to verify which configurations can be deployed. Since these configuration parameters also affect the estimation accuracy, the design of the virtual load sensor is tackled as a co-design problem. The resulting virtual load sensor, which is deployable for real-time execution, achieves an RMS estimation error of 0.6% in a numerical validation, using 4 strain gauges on the ring gear.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.